Many areas of research and clinical practice employ various detection methods and technologies for detecting and measuring concentrations of macro and small molecules, including bio-molecules. Often, it is desirable to perform such detection with great sensitivity, quickly, and/or in a multiplex. Known methods, however, typically sacrifice one or more features in favor of another, depending on the context in which the method is employed.
For example, multiplexed assays typically involve detection of all analytes after a single period of elapsed time. This period is often chosen based on the optimal binding kinetics of one analyte of a plurality of analytes, which necessarily results in detection at a time that is not optimal for the other analytes, based on their binding kinetics. Similarly, known methods may sacrifice the sensitivity of an assay in favor of obtaining a rapid result, or vice versa.
A significant limitation of known assay methods is their inability to distinguish specific binding of an analyte from non-specific binding of non-analyte components of a tested sample. Biological samples, for example, may contain a high concentration of proteins that are not of interest, relative to the concentration of a protein that is of interest, but which may still engage in non-specific binding with a detection label or with a capture agent or other moiety. A single measure of binding (e.g., based on fluorescence of the detection label) will therefore necessarily include both specific binding and non-specific binding components and result in overestimation of the degree of specific binding. In some cases, a signal may be present due to non-specific interactions alone without any specific component. However, a single measure of binding will not be able to distinguish between a true (specific) signal, a false (non-specific) signal, or a mix of both.
Furthermore, non-specific binding can often be relatively stable over time. This leads to significant complications and limitations for applications such as biomarker discovery and validation, wherein non-specific signals can taint results and lead to the expensive and lengthy pursuit of biomarkers that are ultimately determined to be of no value or significance. Additionally, in clinical diagnostic settings, non-specific data leads to higher false positive rates, and limits the ability to accurately quantify biomarker concentrations.